The growth of the Internet and the ability to acquire and retrieve digital content has increased the need for the ability to intelligently access images. Current image search technologies are based either on metadata such as keywords or image features such as overall image features such as RGB or brightness histograms. In addition, the search results are only as good as the keyword provided and the accuracy of the keywords in the database. Although humans can easily determine similarities between images and categorize images, computer systems to date have not provided efficient searching means to deal with large image collections. Current image search technology provide very poor search results with many of the displayed images representing unrelated content and the limited processing speed relegates relevance based image search engines to desktop applications where collections are limited in size.
Accordingly, an improved systems and methods that enable classification and searching of images in an efficient and accurate manner remains highly desirable.